code: def test_dst_disabled():
      """Tests the case where DST is disabled."""
      dense = torch.tensor([0.5000, 0.6000, 0.7000, 0.8000, 0.9000])
      result_rt = torch.tensor([0.6000, 0.7618, 0.7000, 0.6382, 0.8000])
      result_sst = torch.tensor(
          [
              3.50000000000000000000 + 0.00000000000000000000j,
              0.00000000000000000000 + 0.00000000000000000000j,
              -0.25000002980232238770 + 0.08122986555099487305j,
              -0.25000002980232238770 - 0.08122986555099487305j,
              0.00000000000000000000 + 0.00000000000000000000j,
          ]
      )
      sparser = SignalSparsity(sst_top_k_element=3, sst_top_k_dim=0)
      rt, sst, dst = sparser.lossy_compress(dense)
      objects_are_equal(
          rt, result_rt, raise_exception=True, rtol=RTOL, atol=ATOL
      )
      objects_are_equal(
          sst, result_sst, raise_exception=True, rtol=RTOL, atol=ATOL
      )
      assert dst is None
  
file_path: fairscale/tests/experimental/wgit/test_signal_sparsity.py
imports: import pytest
  import torch
  from fairscale.experimental.wgit.signal_sparsity import SignalSparsity, random_sparse_mask
  from fairscale.fair_dev.testing.testing import objects_are_equal
label_desc: Use image node_id 13 for calling a global function with example usage: test_dst_disabled() without return types